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This paper deals with the recovery of a scene from a pair of images, where each image is acquired from a different viewpoint. The central problem is the identification of corresponding points in all views. We use the feature-based approach to find corresponding points.Various types of features have been sued previously, where Gabor features showed significant advantages in terms of accuracy and the complexity/accuracy trade-off. The accuracy is measured as the rate of correctly associated pixels The accuracy measures are found by comparing the disparity maps produced by the matching program with the correct disparities. These correct disparities must be known, and are typically produced by expensive photogrammetric techniques. In this paper we show a method of gauging the performance of a stereo by expensive photogrammetric techniques. In this paper we show a method of gauging the performance of a stereo matcher without the necessity of such a reference disparity date set. We show that statistics on the back-matching distances can be used instead. these are a by- product of the matching process. This opens the door to extensive testing and optimization, since we no longer have to rely on the existence of the reference disparities.
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Wolfgang Poelzleitner, Oliver Sidla, "Accuracy optimization in hierarchical stereo disparity computation using the back-matching distance," Proc. SPIE 3164, Applications of Digital Image Processing XX, (30 October 1997); https://doi.org/10.1117/12.292773